metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: whisper-small-hi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 hi
          type: mozilla-foundation/common_voice_11_0
          config: hi
          split: None
          args: hi
        metrics:
          - name: Wer
            type: wer
            value: 0.330906628290866

whisper-small-hi

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 hi dataset. It achieves the following results on the evaluation set:

Loss: 0.5355
Wer: 0.3309

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0534	4.89	1000	0.3375	0.3465
0.0042	9.78	2000	0.4443	0.3402
0.0002	14.67	3000	0.4973	0.3301
0.0001	19.56	4000	0.5254	0.3309
0.0001	24.45	5000	0.5355	0.3309

Framework versions

Transformers 4.28.0.dev0
Pytorch 2.0.0+cu117
Datasets 2.11.0
Tokenizers 0.13.3